The advent of new high performance tandem mass spectrometers equipped with increasingly sensitive, high-throughput chromatographic systems and the most versatile collision- and electron-based activation methods have catalyzed significant inroads in the field of proteomics. Despite these sweeping advances in instrumentation and methodologies, few are aimed at exploiting the information available from the acidic proteome. To date, proteome characterization by mass spectrometry has overwhelmingly focused on analysis of peptide cations, resulting in an intrinsic bias towards basic peptides that easily ionize under acidic HPLC conditions and positive polarity MS settings. Given that approximately 50% of peptides/proteins are naturally acidic, coupled with the fact that many of the most important PTMs are likewise acidic (e.g., phosphorylation, acetylation, glycosylation, etc.), there is a compelling need for better analytical methodologies for characterization of the acidic proteome. This deficiency in methods is largely due to the lack of tandem MS techniques suitable for efficient and predictable dissociation of peptide anions. We propose to develop an innovative ultraviolet photodissociation (UVPD) strategy that offers the ability to rapidly sequence both peptide cations and anions (implemented in alternating scans), produces rich diagnostic information suitable for database searches, allows post-translational modifications to be pinpointed, and is readily adapted to high throughput LCMS applications. Data processing will be facilitated by the development of new database search and scoring algorithms based on expansion of MassMatrix, a software package for identifying and characterizing proteins and peptides from tandem mass spectrometric data. The development of this high-throughput LC-UVPD-MS strategy for characterization of both acidic and basic peptides for targeted and global proteomics will entail: (1) Systematic optimization and evaluation of UVPD for analysis of peptide cations and anions and integration with robust LCMS conditions. (2) Evaluation of three proteolytic enzymes for enhancement of peptide sequence coverage in the positive and negative modes, including trypsin, Lys-C, and Glu-C, for production of peptides prior to LC-UVPD-MS analysis. (3) Development of database search algorithms for identification of proteins using both positive and negative UVPD mass spectra. We will write script to manipulate the UVPD spectra to make them more applicable to database searching algorithms and expand the capabilities of MassMatrix for negative ions. (4) Application of the new LC- UVPD-MS approach for characterization of mitogen-activated protein kinase (MAPK) pathway proteins, ones that play key roles in cancer progression.